Image pickup system for reducing noise attributable to an image pickup device

ABSTRACT

An image pickup system according to the present invention includes an extracting unit for extracting a block area with a predetermined size from a signal of an image pickup device, a transforming unit for transforming the signal in the extracted block area into a signal in a frequency space, an estimating unit for estimating the amount of noises of a frequency component except for a zero-order component based on the zero-order component in the transformed signal in the frequency space, a noise reducing unit for reducing noises of the frequency component except for the zero-order component based on the estimated amount of noises, and a compressing unit for compressing the zero-order component and the frequency component except for the zero-order component from which the noises are reduced.

CROSS REFERENCE TO RELATED APPLICATION(S)

This application is a divisional of U.S. patent application Ser. No.10/530,085, filed Oct. 3, 2005, which is a 35 U.S.C. 371 submission ofInternational Application No. PCT/JP2003/012653, International FilingDate of Oct. 2, 2003, which claims the priority of Japanese PublishedPatent Application No. 2002-291562, Publication Date of Oct. 3, 2002,which are incorporated by reference as if fully set forth.

FIELD OF INVENTION

The present invention relates to an image pickup system and a replaysystem for reducing random noises due to an image pickup device systemwith high precision in the compression/decompression using the frequencyspace of JPEG or MPEG.

BACKGROUND

Generally, a noise component is included in a digital signal obtainedfrom an image pickup device and an analog circuit accompanied therewithand an A/D converter of the image pickup device and, mainly, isclassified into a fixed pattern noise and a random noise.

The fixed pattern noise is substantially caused by noises from the imagepickup device, typically, a defect pixel.

The random noise is generated in the image pickup device and the analogcircuit with a characteristic approximate to the white noisecharacteristic.

Japanese Unexamined Patent Application Publication No. 2001-157057discloses one technology for adaptively reducing the noises depending ona signal level under the control of the frequency characteristic viafiltering based on an amount N of noises which is estimated for a signallevel D from a function [N=ab^(cD)] where reference symbols a, b, and cdenote statically-given constant terms and the signal level D is aresultant value of the conversion into the concentration level.

Further, Japanese Unexamined Patent Application Publication No.2002-57900 discloses another technology for reducing the noises withoutdeterioration in original signals at the edge thereof by controlling anaverage number n of pixels for moving average which is used as afunction [n=a/(Δ+b)] where reference symbol Δ denotes a differential Δbetween a target pixel and an adjacent one thereof and reference symbolsa and b denote statically-given constant terms and by using no movingaverage when the obtained differential Δ is a predetermined threshold ormore. Further, the signal after the reduction of noises are recorded andstored via the compression using the frequency space of JPEG and MPEGand, in the replay operation, the compressed signals are decompressed.

Both the functions disclosed in Japanese Unexamined Patent ApplicationPublication No. 2001-157057 and Japanese Unexamined Patent ApplicationPublication No. 2002-57900 are defined in real space and the noises arereduced by using the functions in the real space. On the contrary, thesignals are generally compressed/decompressed in the frequency space,independently of the noise reduction.

With the above-mentioned structure, the independent system processing ofthe noise reduction and the compression/decompression causes a problemagainst the low-cost structure of the image pickup system and the replaysystem for fast processing.

The fixedly-given constant terms in the above-mentioned functions do notcorrespond to the partial update of the system or the aging change,thereby causing the inflexibility. Further, the systems according to thetechnologies disclosed in Japanese Unexamined Patent ApplicationPublication No. 2001-157057 and Japanese Unexamined Patent ApplicationPublication No. 2002-57900 have a problem to enable the noise reductiononly with the calculated constant terms for functions.

The present invention is devised in consideration of the abovecircumstances. It is one object of the present invention to provide animage pickup system and a replay system for fast obtaining ahigh-quality image with low costs.

Further, it is another object of the present invention to provide animage pickup system and a replay system for flexibly obtaining ahigh-quality image corresponding to various systems.

SUMMARY

An image pickup system according to the present invention includes anextracting unit for extracting a block area with a predetermined sizefrom a signal of an image pickup device, a transforming unit fortransforming the signal in the extracted block area into a signal in afrequency space, an estimating unit for estimating the amount of noisesof a frequency component except for a zero-order component based on thezero-order component in the transformed signal in the frequency space, anoise reducing unit for reducing noises of the frequency componentexcept for the zero-order component based on the estimated amount ofnoises, and a compressing unit for compressing the zero-order componentand the frequency component except for the zero-order component fromwhich the noises are reduced.

BRIEF DESCRIPTION OF THE DRAWING(S)

FIG. 1 is a block diagram showing the structure of an image pickupsystem according to a first embodiment of the present invention;

FIG. 2 is a block diagram showing the structure of a noise estimatingunit according to the first embodiment;

FIG. 3A is a diagram for explaining one DCT transformation according tothe first embodiment;

FIG. 3B is a diagram for explaining another DCT transformation accordingto the first embodiment;

FIG. 4A is a graph for explaining one formulation of the amount ofnoises according to the first embodiment;

FIG. 4B is a graph for explaining another formulation of the amount ofnoises according to the first embodiment;

FIG. 5A is a graph for explaining one example of a parameter forformulation of the amount of noises according to the first embodiment;

FIG. 5B is a graph for explaining another example of the parameter forformulation of the amount of noises according to the first embodiment;

FIG. 5C is a graph for explaining another example of the parameter forformulation of the amount of noises according to the first embodiment;

FIG. 6 is a block diagram showing the structure of a noise reducing unitaccording to the first embodiment;

FIG. 7A is a flowchart showing one software processing of noisereduction and compression according to the first embodiment;

FIG. 7B is a flowchart showing another software processing of noisereduction and compression according to the first embodiment;

FIG. 8 is a block diagram showing the structure of an image pickupsystem according to a second embodiment of the present invention;

FIG. 9A is a diagram for explaining one wavelet transformation accordingto the second embodiment;

FIG. 9B is a diagram for explaining another wavelet transformationaccording to the second embodiment;

FIG. 9C is a diagram for explaining another wavelet transformationaccording to the second embodiment;

FIG. 10 is a block diagram showing the structure of a noise estimatingunit according to the second embodiment;

FIG. 11 is a block diagram showing the structure of a noise reducingunit according to the second embodiment;

FIG. 12 is a block diagram showing the structure of a replay systemaccording to a third embodiment of the present invention;

FIG. 13A is a flowchart showing one software processing of decompressionand noise reduction according to the third embodiment;

FIG. 13B is a flowchart showing another software processing ofdecompression and noise reduction according to the third embodiment;

FIG. 14 is a block diagram showing the structure of an image pickupsystem according to a fourth embodiment of the present invention; and

FIG. 15 is a flowchart showing software processing of parametercorrection for noise reduction according to the fourth embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT(S)

Hereinbelow, embodiments of the present invention will be described withreference to the drawings.

FIGS. 1 to 7B show the first embodiment of the present invention. FIG. 1is a block diagram showing the structure of an image pickup system. FIG.2 is a block diagram showing the structure of a noise estimating unit.FIGS. 3A and 3B are diagrams for explaining DCT transformations. FIGS.4A and 4B are graphs for explaining formulations of the amount ofnoises. FIGS. 5A to 5C are graphs for explaining parameters forformulation of the amount of noises. FIG. 6 is a block diagram showingthe structure of a noise reducing unit. FIGS. 7A and 7B are flowchartsshowing software processing of noise reduction and compression.

Referring to FIG. 1, the image pickup system comprises: a lens system 1for forming an image of a subject; a stop 2 arranged in the lens system1, for prescribing the transmission range of beams through the lenssystem 1; a low-pass filter 3 for removing an unnecessary high-frequencycomponent from the beams which form the image via the lens system 1; aCCD 4, serving as an image pickup device, for photoelectricallyconverting an optical subject image formed via the low-pass filter 3 andoutputting an electronic video signal; an A/D converter 5 forconverting, into a digital signal, an analog video signal outputted fromthe CCD 4; a first buffer 6 for temporarily storing the digital imagedata outputted from the A/D converter 5; a photometry estimating unit 7for estimating the photometry on the subject by using image data storedin the first buffer 6 and controlling the stop 2 and the CCD 4 based onthe estimating result; a focus detecting unit 8 for detecting the focalpoint by using the image data stored in the first buffer 6 and drivingan AF motor 9, which will be described later, based on the detectingresult; the AF motor 9 for driving a focus lens and the likeincorporated in the lens system 1 under the control of the focusdetecting unit 8; a signal processing unit 10 for reading a video signalstored in the first buffer 6 and performing general signal processingincluding the white balance processing, interpolation, and emphasis; asecond buffer 11 for temporarily storing the video signal processed bythe signal processing unit 10; a block extracting unit 12, serving asblock extracting means, for sequentially reading the video signal storedin the second buffer 11 based on the unit of size of predeterminedblock; a Y/C separating unit 13 for separating, into a luminance signalY and color difference signals Cb and Cr, R, G, B signals based on theunit of block read by the block extracting unit 12; a luminance DCT unit14, serving as transforming means, for transforming the luminance signalY separated by the Y/C separating unit 13 into a frequency spatialsignal by a well-known DCT (Discrete Cosine Transform) transformation; adown-sampling unit 17 for down-sampling the color difference signals Cband Cr separated by the Y/C separating unit 13 by a predetermined ratio;a color difference DCT unit 18, serving as transforming means, fortransforming the color difference signals Cb and Cr down-sampled by thedown-sampling unit 17 into the frequency spatial signal by the DCTtransformation; a zero-order extracting unit 15 for extracting azero-order component from an output of the luminance DCT unit 14 andextracting the zero-order component from the output of the colordifference DCT unit 18; a zero-order quantizing unit 16 for quantizingthe zero-order component extracted by the zero-order extracting unit 15;a noise estimating unit 20, serving as noise estimating means, forestimating the amount of noises of the frequency component except forthe zero-order component from the zero-order components extracted by thezero-order extracting unit 15; a high-frequency extracting unit 19 forextracting the frequency component except for the zero-order componentfrom the luminance DCT unit 14 and further extracting the frequencycomponent except for the zero-order component from the output of thecolor difference DCT unit 18; a noise reducing unit 21, serving as noisereducing means, for reducing the noises with the high-frequencycomponent extracted by the high-frequency extracting unit 19 based onthe amount of noises estimated by the noise estimating unit 20; ahigh-frequency quantizing unit 22 for quantizing the high-frequencycomponent processed by the noise reducing unit 21; a compressing unit23, serving as compressing means, for compressing the output of thezero-order quantizing unit 16 and an output of the high-frequencyquantizing unit 22; an output unit 24 for recording the image datacompressed by the compressing unit 23 to a recording medium such as amemory card; an external I/F unit 26 having an interface to a powerswitch, shutter button, and a mode switch for switching variousphotographing modes; and a control unit 25 serving as both control meansand obtaining means, having a microcomputer for systematicallycontrolling the image pickup system including the photometry estimatingunit 7, the focal point detecting unit 8, the signal processing unit 10,the Y/C separating unit 13, the zero-order extracting unit 15, thezero-order quantizing unit 16, the high-frequency extracting unit 19,the noise estimating unit 20, the noise reducing unit 21, thehigh-frequency quantizing unit 22, the compressing unit 23, the outputunit 24, and the external I/F unit 26 connected interactively thereto.

Next, a description is given of the signal flow in the image pickupsystem shown in FIG. 1.

In the image pickup system, the photographing condition such the ISOsensitivity is set via the external I/F unit 26. After the photographingcondition, the shutter button serving as a two-step pressing buttonswitch is half pressed, thereby entering a pre-image-pickup mode.

The optical image formed via the lens system 1, the stop 2, and thelow-pass filter 3 photographed by the CCD 4, is outputted as an analogvideo signal, is converted into a digital signal by the A/D converter 5,and is transferred to the first buffer 6.

According to the first embodiment, the CCD 4 is a single-plate primarycolor CCD having primary color R, G, and B filters in front of the imagepickup surface.

Then, the video signal in the first buffer 6 is transferred to thephotometry estimating unit 7 and the focal point detecting unit 8.

The photometry estimating unit 7 obtains the luminance level in theimage, calculates a best exposure value in consideration of the set ISOsensitivity and shutter speed of the limit of image stabilizer, andcontrols the electronic shutter speed of the CCD 4 and a stop value ofthe stop 2 to obtain the best exposure value.

The focal point detecting unit 8 detects the edge emphasis in the image,and controls the AF motor 9 so that the edge emphasis is maximum toobtain the focused image.

Through the pre-image-pickup mode, the preparation for photographingends. Next, the entire press of the shutter button is detected via theexternal I/F unit 26 and then the photographing operation is performed.

The photographing operation is performed under the exposure conditionobtained by the photometry estimating unit 7 and the focusing conditionobtained by the focal point detecting unit 8. The conditions in thephotographing operation are transferred to the control unit 25 servingas the obtaining means.

After the photographing operation, the video signal is transferred andstored to the first buffer 6, similarly to the pre-image-pickup mode.

The video signal in the first buffer 6 is transferred to the signalprocessing unit 10, is subjected to the well-known white balancingprocessing, interpolation, and emphasis, and is transferred to thesecond buffer 11.

The block extracting unit 12 sequentially reads the video signal storedin the second buffer 11 with a predetermined block size, e.g., a unitblock containing 8×8 pixels, under the control of the control unit 25,and transfers the read signals to the Y/C separating unit 13.

The Y/C separating unit 13 converts the video signal comprising the R,G, and B signals from the block extracting unit 12 into the luminancesignal Y and the color difference signals Cb and Cr based on convertingformulae as shown in the following Formula 1.Y=0.29900R+0.58700G+0.11400BCb=−0.16874R−0.33126G+0.50000BCr=0.50000R−0.41869G−0.08131B  [Formula 1]

The luminance signal Y generated by the Y/C separating unit 13 istransferred to the luminance DCT unit 14, and the color differencesignals Cb and Cr are transferred to the down-sampling unit 17.

The down-sampling unit 17 down-samples the color difference signals Cband Cr by a predetermined ratio, and then transfers the sampled signalsto the color difference DCT unit 18.

As mentioned above, the luminance DCT unit 14 and the color differenceDCT unit 18 performs the well-known DCT (Discrete Cosine Transform)transformation, thereby transforming the video signal in the real spaceinto the signal in the frequency space.

The signal transformed into the frequency space is subjected to thenoise reduction and the compression in the order of the luminance signalY and the color difference signals Cb and Cr based on the control of thecontrol unit 25 as follows.

First, the zero-order extracting unit 15 extracts the zero-ordercomponent from the signal in the frequency space transformed by theluminance DCT unit 14 and the color difference DCT unit 18.

Next, the zero-order quantizing unit 16 quantizes the zero-ordercomponent extracted by the zero-order extracting unit at a predeterminedinterval.

The compressing unit 23 compresses the zero-order component after thequantization by the well-known Huffman coding and arithmetic coding. Theabove-compressed signals are sequentially transferred to the output unit24, and are stored in the memory card as mentioned above.

The noise estimating unit 20 obtains the zero-order component from thezero-order extracting unit 15, obtains the image in the photographingoperation from the control unit 25, and calculates the amount of noisesof the frequency component except for the zero-order component based onthe information.

The high-frequency extracting unit 19 extracts the frequency componentexcept for the zero-order component from the signal in the frequencyspace transformed by the luminance DCT unit 14 and the color differenceDCT unit 18.

The noise reducing unit 21 reduces the noises of the frequency componentexcept for the zero-order component from the high-frequency extractingunit 19 based on the amount of noises from the noise estimating unit 20.

The high-frequency quantizing unit 22 quantizes the high-frequencycomponent subjected to the noise reduction of the noise reducing unit 21at a predetermined interval.

The compressing unit 23 compresses the high-frequency componentquantized by the high-frequency quantizing unit 22 by the well-knownHuffman coding or arithmetic coding, similarly to the zero-ordercomponent quantized by the zero-order quantizing unit 16. The compressedsignal is sequentially transferred to the output unit 24, and is storedin the memory card as mentioned above. The compressing unit 23 performsthe well-known JPEG compression.

The processing of the Y/C separating unit 13, the zero-order extractingunit 15, the zero-order quantizing unit 16, the high-frequencyextracting unit 19, the noise estimating unit 20, the noise reducingunit 21, the high-frequency quantizing unit 22, and the compressing unit23 is performed under the control of the control unit 25, synchronouslywith the operation for extracting the block of the block extracting unit12 based on the unit of block.

Next, an example of the structure of the noise estimating unit 20 willbe described with reference to FIG. 2.

The noise estimating unit 20 comprises: a standard value giving unit 31,serving as giving means, for transferring the standard temperature ofthe CCD 4 to a coefficient calculating unit 32, which will be describedlater; a ROM 33 for parameter, serving as coefficient calculating means,for storing a parameter of a function, which will be described later,for estimating the amount of noises; a coefficient calculating unit 32,serving as coefficient calculating means, for calculating a coefficientof a predetermined formula for estimating the amount of noises of thehigh-frequency component except for the zero-order component based onthe parameter from the ROM 33 for parameter, the zero-order componentfrom the zero-order extracting unit 15, the gain from the control unit25, and the temperature information from the standard value giving unit31; and a noise calculating unit 34, serving as noise calculating means,for calculating the amount of noises by using a formulated function,which will be described later, with the coefficient calculated by thecoefficient calculating unit 32 and transferring the amount of noises tothe noise reducing unit 21.

The standard value giving unit 31, the coefficient calculating unit 32,and the noise calculating unit 34 are interactively connected to thecontrol unit 25 for control operation. The control unit 25 determinesgain of the signal from the photometry estimating unit 7 or signalprocessing unit 10, and transfers the gain to the coefficientcalculating unit 32.

Herein, a description is given of the order component for DCTtransformation to the frequency space with reference to FIGS. 3A and 3B.FIG. 3A shows a block having 8×8 pixels in the real space. FIG. 3B showsa block having 8×8 pixels in the frequency space.

Referring to FIG. 3A, the signal in the pixel block in the real space issubjected to the DCT transformation, thereby obtaining the component ofthe pixel block in the frequency space shown in FIG. 3B. Referring toFIG. 3B, the frequency space has the origin on the upper left, that is,zero-order component, and the high-frequency component of primary ormore on the coaxial position with the origin as the center. Thezero-order extracting unit 15 performs the processing for extracting, asthe zero-order component, the pixel on the upperleft in the frequencyspace shown in FIG. 3B.

Next, a description is given of the formulation of the amount of noiseswith reference to FIGS. 4A and 4B. FIG. 4A shows the plotting of anamount N of noises for a zero-order component L, serving as a formulatedfunction shown in Formula 2.N=AL ^(B) +C  [Formula 2]

where reference symbols A, B, and C denote constant terms. This formula2 is obtained by adding the constant term to a function of the power ofthe zero-order component L.

However, the amount N of noises does not depend on only the zero-ordercomponent L of the signal value level. In addition, the amount N ofnoises varies depending on the temperature of the CCD 4 serving as theimage pickup device and the gain of signal. Therefore, the factors areconsidered in the example shown in FIG. 4B.

That is, in place of the constant terms A, B, and C in Formula 2, threefunctions a(T, G), b(T, G), and c(T, G) using the parameters of thetemperature T and the gain G are introduced in Formula 3.N=a(T,G)L ^(b(T,G)) +c(T,G)  [Formula 3]

FIG. 4B shows a curve of Formula 3 plotted by using a plurality oftemperatures T (T1 to T3 in the drawing) and a plurality of gains G (1,2, and 4 times in the drawing).

Referring to FIG. 4B, an independent variable is the zero-ordercomponent L, a dependent variable is the amount N of noises, and thetemperature T serving as the parameter is plotted as the coordinates inthe direction orthogonal to the variables. Therefore, the amount N ofnoises using the zero-order component L is read on the plane of T=T1, onthe plane of T=T2, and on the plane of T=T3. In this case, the change incurve due to the gain G serving as the parameter is indicated by aplurality of curves on the planes.

The curves shown by the parameters are approximate to the curve ofFormula 2 as shown in FIG. 4A. Obviously, the coefficients A, B, and Cobtained from the functions a, b, and c differ depending on the value ofthe temperature T or the gain G.

FIG. 5A schematically shows the characteristic of the function a(T, G).FIG. 5B schematically shows the characteristic of the function b(T, G).FIG. 5C schematically shows the characteristic of the function c(T, G).

The functions use two variables of independent variables of thetemperature T and the gain G. FIGS. 5A to 5C show curves in the spaceplotted as three-dimensional coordinates. However, the change incharacteristic is shown here by using the curves, in place of showingthe specific curve shapes.

The temperature T and the gain G are inputted to the functions a, b, andc as the parameters, thereby outputting the constant terms A, B, and C.The specific shapes of the functions are easily obtained by measuring,in advance, the characteristics of the image pick-up system includingthe CCD 4.

The coefficient calculating unit 32 obtains the constant terms A, B, andC from the three functions a, b, and c recorded to the ROM 33 forparameter by using, as the input parameters, the gain G from the controlunit 25 and the temperature T from the standard value giving unit 31,and transfers the obtained constant terms A, B, and C to the noisecalculating unit 34.

The noise calculating unit 34 calculates the amount N of noises based onthe Formula 2 by using the zero-order component L from the coefficientcalculating unit 32 and the constant terms A, B, and C, and transfersthe calculated amount N of noises to the noise reducing unit 21.

In the foregoing, the temperature of the CCD 4 serving as the imagepickup device is fixedly given from the standard value giving unit 31.However, the present invention is not limited to this. For example,temperature information may be obtained in real time by arranging atemperature sensor near the CCD 4 and may be transferred to the controlunit 25 serving as obtaining means. On the contrary, when the gain G isnot dynamically obtained, a predetermined value may be given from thestandard value giving unit 31.

The formulation of the amount of noises uses the function of the powershown in Formula 2. However, the present invention is not limited tothis. The formulation is possible by using a quadratic formula of[N=AL²+BL+C]. Further, a polynominal or sprine function may be used.

Next, a description is given of one example of the structure of thenoise reducing unit 21 with reference to FIG. 6.

The noise reducing unit 21 comprises: a determining unit 41, serving asselecting means, for estimating a threshold n of the high-frequencycomponent in which the information is not stored, based on informationon an image quality mode (including information of a compressing ratio)from the control unit 25; an average calculating unit 42, serving asaverage calculating means, for calculating an average AV of thefrequency component except for the zero-order component transferred fromthe high-frequency extracting unit 19; an allowable range setting unit43, serving as allowable range setting means, for setting an upper limitTup and a lower limit Tlow of the high-frequency component, which willbe described later, by using the average AV from the average calculatingunit 42 and the amount N of noises from the noise estimating unit 20; aseparating unit 44, serving as frequency separating means, forextracting the high-frequency component within a predetermined frequencyband from the frequency components except for the zero-order componenttransferred from the high-frequency extracting unit 19; and a correctingunit 45, serving as correcting means, for reducing the noises of thefrequency components within the frequency and extracted by theseparating unit 44 based on the upper limit Tup and the lower limit Tlowfrom the allowable range setting unit 43 and the threshold n from thedetermining unit 41 and transferring the processed frequency to thehigh-frequency quantizing unit 22. The determining unit 41, the averagecalculating unit 42, the allowable range setting unit 43, the separatingunit 44, and the correcting unit 45 are interactively connected to thecontrol unit 25 for control operation.

The separating unit 44 extracts the high-frequency component within thepredetermined frequency band based on the control unit 25, as mentionedabove, and transfers the extracted component to the correcting unit 45.In the DCT transformation, referring to FIG. 3B, the high-frequencycomponent within the predetermined frequency band is arranged coaxiallywith the origin at the upper left. Therefore, the separating unit 44sequentially extracts the high-frequency component of primary or morebased on the arrangement.

The allowable range setting unit 43 sets, based on the following Formula4, the upper limit Tup and lower limit Tlow for the high-frequencycomponent based on the amount N of noises from the noise estimating unit20 and the average AV from the average calculating unit 42, andtransfers the set values to the correcting unit 45.Tup=AV+N/2Tlow=AV−N/2  [Formula 4]

The determining unit 41 obtains, from the control unit 25, theinformation on the image quality mode set by the external I/F unit 26,and further obtains the corresponding compressing ratio from the imagequality mode. The determining unit 41 estimates the threshold n of thehigh-frequency component which does not store the information, namely,the high-frequency component which does not store the noise component,and transfers the threshold n to the correcting unit 45.

The correcting unit 45 performs the processing of the frequencycomponents from the separating unit 44 based on the threshold n from thedetermining unit 41 and the upper limit Tup and the lower limit Tlowfrom the allowable range setting unit 43. First, the correcting unit 45processes only the frequency component with the order lower than then-th order serving as the target of noise reduction based on thethreshold n from the determining unit 41. And the correcting unit 45outputs, to the high-frequency quantizing unit 22, the frequencycomponent with the order higher than the n-th order without anyprocessing. When the frequency component is the n-th order component orless, the correcting unit 45 selects, for an element S of the frequencycomponent, any of three processing shown in the following Formula 5based on the upper limit Tup and the lower limit Tlow, and corrects anelement S.S=S−N/2(Tup<S)S=AV(Tlow≦S≦Tup)S=S+N/2(S<Tlow)  [Formula 5]

The correcting unit 45 sequentially outputs, to the high-frequencyquantizing unit 22, the element of the frequency component subjected tothe correction of Formula 5.

In the foregoing, the processing is performed in the hardware manner.However, the present invention is not limited to this and the processingmay be performed in the software manner. For example, the signal fromthe CCD 4 is set as Raw data without any processing, and the temperaturein the photographing operation and the gain from the control unit 25 areadded as header information to the Raw data. The Raw data with theheader information may be processed on another software.

A description is given of the software processing of noise reduction andcompression with reference to FIGS. 7A and 7B. FIGS. 7A and 7B showdivided software processing.

Starting the processing, the video signal obtained as the Raw data andthe header information serving as the temperature and the gain are readto the computer (in step S1). The header information is used inprocessing in steps S13 and S15, which will be described later.

Next, the read Raw data is subjected to general signal processing ofwhite balance processing, interpolation, and emphasis (in step S2). Ablock area with a predetermined size, e.g., a block area with 8×8 pixelsunit is extracted from the signal after processing (in step S3).

The video signals (R, G, and B signals) of the pixel in the block areconverted into the luminance signal Y and the color difference signalsCb and Cr (in step S4).

Next, the luminance signal Y is transformed into the signal in thefrequency space by the DCT transformation (in step S5). Then, referringto FIG. 7B, the processing advances to steps S11 and S12. The processingshown in FIG. 7B will be described later.

At the timing until the processing in step S21 shown in FIG. 7B, theprocessing shifts to that shown in FIG. 7A, and the luminance signal Ysubjected to the compression and noise reduction is outputted (in stepS6).

The color difference signals Cb and Cr separated in step S4 aredown-sampled by a predetermined ratio (in step S7), and the signals aretransformed into the signals in the frequency space by the DCTtransformation (in step S8). Then, the processing shifts to steps S11and S12 (refer to FIG. 7B).

At the timing of the processing in step S21 shown in FIG. 7B, theprocessing shifts to that shown in FIG. 7A again and the colordifference signals Cb and Cr subjected to the compression and noisereduction are outputted (in step S9).

After ending the processing in steps S6 and S9, it is determined whetheror not the processing ends for the entire blocks (in step S10). If theprocessing does not end, the processing returns to step S3 whereupon theabove-mentioned operation is repeated. If it is determined in step S10that the processing ends for the entire blocks, the processing ends.

Next, a description is given of the compression and noise reductionshown in FIG. 7B. The processing is commonly performed for the luminancesignal Y and the color difference signals Cb and Cr.

The zero-order component is extracted from the component transformed inthe frequency space through the processing in step S5 or S8 (step S11).The high-frequency component except for the zero-order component isextracted (step S12).

Next, it is determined whether or not the noise is reduced based on theheader information read in step S1 (step S13).

If it is determined that the noise is reduced, the average of thehigh-frequency component is calculated (in step S14).

The amount of noises is calculated based on Formula 2 by using thezero-order component extracted in step S11 and the header informationread in step S1 (in step S15).

Then, the allowable range is set based on Formula 4 (step S16). Thenoise is reduced based on Formula 5 (in step S17).

Upon ending the processing in step S17, or when it is determined in stepS13 that the noise is not reduced, it is determined whether or not theprocessing ends for the entire high-frequency components (in step S18).If it is determined that the processing does not end for the entirehigh-frequency components, the processing returns to step S12 whereuponthe next high-frequency is subjected to the above-mentioned processing.

When it is determined that the processing ends for the entirehigh-frequency components, the high-frequency component is quantized (instep S20).

The zero-order component extracted in step S11 is quantized (in stepS19).

After ending the quantizing processing in steps S19 and S20, thequantized zero-order component and the high-frequency component arecompressed (in step S21). Then, the processing shifts to that shown inFIG. 7A.

In the foregoing, the primary color single-plate CCD is used as oneexample. However, the present invention is not limited to this and maybe a complementary-color single-plate CCD. Further, a two-plate CCD orthree-plate CCD may be used.

According to the first embodiment, the compression and the noisereduction using the frequency space are integrated, thereby structuringan image pickup system with a high image quality and low costs.

Various parameters including the zero-order component on the amount ofnoises and the temperature and gain of the image pickup device in thephotographing operation are dynamically obtained every photographingoperation, and the amount of noises is calculated based on theparameters. Therefore, the amount of noises is estimated with highprecision. Then, the amount of necessary memories is small by using thefunction upon calculating the amount of noises, and further the costsare low.

In addition, the upper limit and the lower limit are set based on theestimated amount of noises and the average of the frequency component,and the noise component is corrected. Therefore, only the noisecomponent is removed and the signal except for the noises is stored asthe original signal. Thus, the image with high quality, from which onlythe noises are reduced, is obtained.

Only the signal having the estimated amount of noises or less issubjected to the smoothing processing and therefore the noises areeffectively reduced.

Further, when the parameters such as the temperature and the gainnecessary for calculating the amount of noises are not obtained, thestandard value is used and therefore the noise reduction is alwaysexecuted. In addition, the parameter calculation is intentionallyomitted, thereby structuring the image pickup system with low costs andlow power consumption.

The signal of the frequency component is separated into the frequencybands and it is selected, depending on the compressing ratio, whether ornot the noise reduction is performed every frequency band. Thehigh-frequency component which is removed by the compression is notsubjected to the noise reduction. Only the necessary frequency band issubjected to the noise reduction and therefore the processing is fast.

FIGS. 8 to 11 show the second embodiment of the present invention. FIG.8 is a block diagram showing the structure of an image pickup system.FIGS. 9A to 9C are diagrams for explaining the wavelet transformation.FIG. 10 is a block diagram showing the structure of the noise estimatingunit. FIG. 11 is a block diagram showing the structure of the noisereducing unit.

According to the second embodiment, the same portions are designated bythe same reference numerals according to the first embodiment, and arenot described. Mainly, different points are described.

Referring to FIG. 8, the image pickup system according to the secondembodiment is approximately similar to that shown in FIG. 1 according tothe first embodiment and, however, additionally has a Wavelettransforming unit 50 serving as transforming means and excludes theluminance DCT unit 14, the down-sampling unit 17, and the colordifference DCT unit 18. The Wavelet transforming unit 50 processes theoutput from the Y/C separating unit 13, and outputs the processingresult to the zero-order extracting unit 15 and the high-frequencyextracting unit 19.

The operation of the above-mentioned image pickup system is basicallythe same as that according to the first embodiment. Only differentportions are described in accordance with the signal flow shown in FIG.8.

The luminance signal Y and the color difference signals Cb and Crobtained by the Y/C separating unit 13 are transferred to the Wavelettransforming unit 50, and are transformed into the frequency space bythe Wavelet transforming unit 50.

FIGS. 9A, 9B, and 9C show the states of Wavelet transformation of theWavelet transforming unit 50.

FIG. 9A shows the block having the 8×8 pixels in the real space.

FIG. 9B shows the block having the 8×8 pixels in the frequency space asa result of one-time Wavelet transformation of that shown in FIG. 9A.Referring to FIG. 9B, the 4×4 pixels at the upper left indicate thezero-order component L with the origin at the upper left, other 4×4pixels indicate the primary high-frequency component, namely, the 4×4pixels at the upper right indicate a primary horizontal component Hh1,4×4 pixels at the lower left indicate a primary vertical component Hv1,and 4×4 pixels at the lower right indicate a primary diagonal componentHs1.

FIG. 9C shows the block having the 8×8 pixels in the frequency space asa result of two-time Wavelet transformation of that shown in FIG. 9A,that is, as a result of one-time Wavelet transformation of thezero-order component L shown in FIG. 9B. Referring to FIG. 9C, in the4×4 pixels at the upper left, the 2×2 pixels at the upper left indicatethe zero-order component L, other pixels indicate the secondaryhigh-frequency component, namely, the 2×2 pixels at the upper rightindicate a secondary horizontal component Hh2, the 2×2 pixels at thelower left indicate a secondary vertical component Hv2, and 2×2 pixelsat the lower right indicate a secondary diagonal component Hs2.According to the second embodiment, as shown in FIG. 9C, a descriptionis given of the frequency space obtained by two-time Wavelettransformation as an example.

From the signal transformed into the signal in the frequency space bythe Wavelet transforming unit 50, the zero-order component is extractedby the zero-order extracting unit 15. Further, the high-frequencyextracting unit 19 extracts the high-frequency component. Similarly tothe first embodiment, the compression and noise reduction are performed.

Hereinbelow, a description is given of one example of the structure ofthe noise estimating unit 20 with reference to FIG. 10.

The noise estimating unit 20 according to the second embodimentcomprises: a standard value giving unit 51, serving as giving means, fortransferring the standard temperature of the CCD 4 to a look-up tableunit 52, which will be described later; and the look-up table unit 52,serving as look-up table means, for holding a look-up table whichrecords a relationship of the amount of noises among the zero-ordercomponent from the zero-order extracting unit 15, the temperature fromthe standard value giving unit 51, the gain from the control unit 25,and for outputting, to the noise reducing unit 21, the amount of noisesobtained by referring to the look-up table. The standard value givingunit 51 and the look-up table unit 52 are interactively connected to thecontrol unit 25 for control operation.

The operation with the above-mentioned structure is as follows.

The zero-order extracting unit 15 extracts the zero-order componentunder the control of the control unit 25, and transfers the extractedcomponent to the look-up table unit 52. The control unit 25 obtains thegain of the signal based on the result of estimating the photometry fromthe photometry estimating unit 7 and the set value of the signalprocessing unit 10, and transfers the obtained gain to the look-up tableunit 52. Further, the standard value giving unit 51 transfers thestandard temperature of the image pickup device to the look-up tableunit 52.

The look-up table unit 52 holds the look-up table for recording therelationship among the zero-order component, the temperature, the gain,and the amount of noises, and comprises the means similar to thataccording to the first embodiment. The look-up table unit 52 refers tothe look-up table by using the zero-order component from the zero-orderextracting unit 15, the temperature from the standard value giving unit51, and the gain from the control unit 25, obtains the amount of noises,and transfers the obtained amount of noises to the noise reducing unit21.

According to the second embodiment, as shown in FIG. 9C, four amounts ofnoises are calculated corresponding to the zero-order component 2×2pixels (namely, four pixels). The calculated amount of noises is usedfor the high-frequency component as follows. First, the high-frequencycomponent is the secondary high-frequency component (secondaryhorizontal component Hh2, secondary vertical component Hv2, or secondarydiagonal component Hs2), then, the block comprises the 2×2 pixels, andthe amount of noises is used for the pixel corresponding to the positionwith a one-to-one corresponding relationship. The high-frequencycomponent is the primary high-frequency component (primary horizontalcomponent Hh1, primary vertical component Hv1, or primary diagonalcomponent Hs1), then, the block comprises the 4×4 pixels, the amount ofnoises of one pixel is enlarged by two times in the vertical andhorizontal direction, and it is used for the unit of 2×2 pixels.

Next, a description is given of one example of the structure of thenoise reducing unit 21 with reference to FIG. 11.

The noise reducing unit 21 according to the second embodiment comprises:a horizontal line extracting unit 61, serving as frequency separatingmeans, for extracting the horizontal line from the high-frequencycomponent except for the zero-order component extracted by thehigh-frequency extracting unit 19; a first smoothing unit 62, serving assmoothing means, for smoothing the horizontal line extracted by thehorizontal line extracting unit 61; a buffer 63 for temporarily storingthe smoothing result of the first smoothing unit 62; a vertical lineextracting unit 64, serving as frequency separating means, for reading,in the vertical direction, the data through the smoothing processing inthe horizontal direction stored in the buffer 63; a second smoothingunit 65, serving as smoothing means, for smoothing the line in thevertical direction read by the vertical line extracting unit 64 and foroutputting the smoothed line to the high-frequency quantizing unit 22; athreshold setting unit 66, serving as threshold setting means, forsetting a threshold in the smoothing operation based on the noise valueestimated by the noise estimating unit 20 and for outputting the setthreshold to the first smoothing unit 62 and the second smoothing unit65; and a determining unit 67, serving as selecting means, forestimating the threshold n serving as the high-frequency component whichdoes not store the information based on the image quality mode obtainedfrom the control unit and for outputting the estimated threshold n tothe first smoothing unit 62 and the second smoothing unit 65.

The horizontal line extracting unit 61, the vertical line extractingunit 64, the threshold setting unit 66, and the determining unit 67 areinteractively connected to the control unit 25 for control operation.

The operation of the noise reducing unit 21 with the above-mentionedstructure is as follows.

The horizontal line extracting unit 61 individually extracts threehigh-frequency component horizontal Hhi, vertical Hvi, and diagonal Hsi(i=1 and 2) based on the unit of horizontal line from the high-frequencyextracting unit 19 under the control of the control unit 25, andtransfers the extracted high-frequency component to the first smoothingunit 62.

The threshold setting unit 66 obtains, from the noise estimating unit20, the corresponding amount of noises of the high-frequency componentbased on the unit of horizontal line extracted by the horizontal lineextracting unit 61 under the control of the control unit 25, andtransfers the obtained amount of noises used as the threshold to thefirst smoothing unit 62.

The determining unit 67 obtains, from the control unit 25, theinformation on the image quality mode set by the external I/F unit 26,and obtains the corresponding compressing ratio from the image qualitymode. Further, the determining unit 67 estimates the threshold n of thehigh-frequency component which does not store the information by theobtained compressing ratio, namely, of the high-frequency componentwhich does not store the noise component, and transfers the threshold nto the first smoothing unit 62 and the second smoothing unit 65.

The first smoothing unit 62 reduces the noises of only the frequencycomponent of the n-th order component or less based on the threshold nobtained from the determining unit 67 and outputs the frequencycomponent of the number of orders higher than the n-th order to thebuffer 63 without processing. When the frequency component is the n-thorder component or less, the first smoothing unit 62 scans thehigh-frequency component from the horizontal line extracting unit 61based on the unit of pixel, and performs, e.g., a well-known hysteresissmoothing of the threshold, as the amount of noises, from the thresholdsetting unit 66. The result of hysteresis smoothing is sequentiallyoutputted and is stored in the buffer 63.

The operation of hysteresis smoothing of the first smoothing unit 62 issynchronized with the operation of the noise estimating unit 20 and theoperation of the threshold setting unit 66 under the control of thecontrol unit 25.

The entire high-frequency components outputted from the high-frequencyextracting unit 19 is processed by the first smoothing unit 62, thevertical line extracting unit 64 individually extracts the threehigh-frequency component horizontal Hhi, vertical Hvi, and diagonal Hsi(i=1 and 2) from the buffer 63 based on the unit of vertical line underthe control of the control unit 25, and transfers the extractedcomponents to the second smoothing unit 65.

The threshold setting unit 66 obtains, from the noise estimating unit20, the corresponding amount of noises of the high-frequency componentbased on the unit of vertical line extracted by the vertical lineextracting unit 64 under the control of the control unit 25, andtransfers the obtained amount of noises as the threshold to the secondsmoothing unit 65.

The second smoothing unit 65 does not perform the processing of the highfrequency component of the number of order higher than n based on thethreshold n obtained from the determining unit 67, and outputs thefrequency component to the high-frequency quantizing unit 22. When thefrequency component is n-th order component or less, the secondsmoothing unit 65 scans the high-frequency component from the verticalline extracting unit 64 based on the unit of pixel, and performs, e.g.,well-known hysteresis smoothing processing of the high-frequencycomponent by using the threshold from the threshold setting unit 66 asthe amount of noises. The result of hysteresis smoothing processing issequentially outputted to the high-frequency quantizing unit 22.

The operation of hysteresis smoothing of the second smoothing unit 65 issynchronized with the operation of the noise estimating unit 20 and theoperation of the threshold setting unit 66 under the control of thecontrol unit 25.

Then, similarly to the first embodiment, the compressing unit 23compresses the signal, and the output unit 24 records and stores thecompressed signal to the memory card or the like. The compression inthis time is performed in conformity with well-known JPEG2000.

As mentioned above, the noise reduction uses the hysteresis smoothing.However, the present invention is not limited to this. For example, thenoise reduction shown by Formula 5 can be applied similarly to the firstembodiment.

According to the second embodiment, the compression using the frequencyspace and the noise reduction are integrated, thereby structuring theimage pickup system for obtaining the high-quality image with low costs.

Further, various parameters including the zero-order component on theamount of noises and the temperature and gain of the image pickup devicein the photographing operation are dynamically obtained everyphotographing operation, and the amount of noises is calculated by usingthe table based on the parameters. Therefore, the amount of noises isestimated with high precision and high speed.

The amount of noises is determined as the threshold and only the signalhaving the threshold or less is subjected to the smoothing processing.Therefore, the signal except for the noise component is stored as theoriginal signal and the image with the high quality from which only thenoises are reduced is obtained.

Further, when the parameters such as the temperature and the gainnecessary for calculating the amount of noises are not obtained, thenoises are always reduced by using the standard value. In addition, thecalculation of one part of parameters is intentionally omitted, therebystructuring the image pickup system with low costs and low powerconsumption.

The noises of only necessary frequency band are reduced depending on thecompressing ratio, thereby increasing the speed of processing.

FIGS. 12, 13A, and 13B show the third embodiment of the presentinvention. FIG. 12 is a block diagram showing the structure of a replaysystem. FIGS. 13A and 13B are flowcharts showing the software processingof noise reduction and decompression.

The third embodiment relates to the replay system, and the componentsfor noise reduction are the same as those according to the first andsecond embodiments. Therefore, the same components are designated by thesame reference numerals, a description thereof is omitted, and differentpoints are mainly described.

It is assumed for decompression that the R, G, and B signals through theJPEG compression described according to the first embodiment aredecompressed. Further, it is assumed that the information in thephotographing operation is written to the header portion.

Similarly to FIG. 1, the replay system comprises: the zero-orderextracting unit 15; the high-frequency extracting unit 19; the noiseestimating unit 20; the noise reducing unit 21; the output unit 24; thecontrol unit 25; and the external I/F unit 26. Further, the replaysystem comprises: an input unit 71 for reading the compressed signalstored in the recording medium such as the memory card; a decompressingunit 72, serving as decompressing means, for decompressing thecompressed signal from the input unit 71 and outputting the decompressedsignal to the zero-order extracting unit 15 and the high-frequencyextracting unit 19; a luminance inverting DCT unit 73, serving asinverting transforming means, for inverting-DCT-transforming theluminance component of the zero-order component from the zero-orderextracting unit 15 and the luminance component of the high-frequencycomponent from which the noises are reduced from the noise reducing unit21; a color difference inverting DCT unit 74, serving as invertingtransforming means, for inverting-DCT transforming the color differencecomponent of the zero-order component from the zero-order extractingunit 15 and the color difference component of the high-frequencycomponent from which the noises are reduced from the noise reducing unit21; an up-sampling unit 75 for up-sampling the color differencecomponent from the color difference inverting DCT unit 74; and a Y/Csynthesizing unit 76 for synthesizing the luminance component of theluminance inverting DCT unit 73 and the color difference component fromthe up-sampling unit 75 to generate the R, G, and B signals and foroutputting the R, G, and B signals to the output unit 24 serving as adisplay device, e.g., a CRT monitor or a liquid crystal monitor.

The input unit 71, the decompressing unit 72, the zero-order extractingunit 15, the high-frequency extracting unit 19, the noise estimatingunit 20, the noise reducing unit 21, the Y/C synthesizing unit 76, theoutput unit 24, and the external I/F unit 26 are interactively connectedto the control unit 25 comprising a microcomputer for control operation.

The external I/F unit 26 according to the third embodiment comprisesinterfaces of a power switch and a reading button.

Next, a description is given of the signal flow of the replay systemshown in FIG. 12.

The reading button is operated via the external I/F unit 26, therebyreading, from the input unit 71, the compressed signal stored in thereading medium such as a memory card.

The compressed signal is transferred to the decompressing unit 72, issubjected to the decompression based on the Huffman coding or arithmeticcoding, and is transformed into the signal in the frequency space.

The zero-order extracting unit 15 extracts the zero-order component fromthe signal in the frequency space, and transfers the extracted signal tothe noise estimating unit 20.

The noise estimating unit 20 receives, from the control unit 25, theinformation in the photographing operation recorded as the headerinformation of the image, calculates the amount of noises of thefrequency component except for the zero-order component similarly to thefirst embodiment, and transfers the calculated amount of noises to thenoise reducing unit 21.

The high-frequency extracting unit 19 extracts the frequency componentexcept for the zero-order component from the signal in the frequencyspace decompressed by the decompressing unit 72, and transfers theextracted component to the noise reducing unit 21.

Similarly to the first embodiment, the noise reducing unit 21 reducesthe noises of the frequency component except for the zero-ordercomponent from the high-frequency extracting unit 19 based on the amountof noises from the noise estimating unit 20.

The zero-order component extracted by the zero-order extracting unit 15and the high-frequency component through the noise reduction by thenoise reducing unit 21 are transferred to the luminance inverting DCTunit 73 or the color difference inverting DCT unit 74, and aretransferred into the signal in the real space. In this case, theluminance signal and the color difference signal are switched under thecontrol of the control unit 25, and are processed based on the unit ofblock obtained from the decompressing unit 72.

The luminance signal from the luminance inverting DCT unit 73 istransferred to the Y/C synthesizing unit 76. The color difference signalfrom the color difference inverting DCT unit 74 is up-sampled by apredetermined ratio by the up-sampling unit 75, and then is transferredto the Y/C synthesizing unit 76.

The Y/C synthesizing unit 76 synthesizes the luminance signal based onthe unit of block and the color difference signal based on the unit ofblock on the basis of the following Formula 6 under the control of thecontrol unit 25 when the luminance signal and the color differencesignal are collected, and generates the R, G, and B signals.R=Y+1.40200CrG=Y−0.34414Cb−0.71414CrB=Y+1.77200Cb−0.41869Cr  [Formula 6]

The R, G, and B signals generated by the Y/C synthesizing unit 76 aresequentially transferred to the buffer in the output unit 24.

The reading processing is executed in the hardware and, however, thepresent invention is not limited to this. For example, the compressedsignal stored in the recording medium such as a memory card and theheader information such as the temperature and the gain in thephotographing operation may be read in a computer and may be processedindependently on software.

Next, a description is given of the software processing fordecompression and noise reduction with reference to FIGS. 13A and 13B.FIG. 13A shows the main flow of the software processing. FIG. 13B showsthe common processing between the luminance signal and the colordifference signal.

Referring to FIG. 13A, starting the processing, first, the compressedsignal and the header information such as the temperature and the gainare read (in step S31). The read header information is transferred tothe processing in steps S41 and S43, which will be described later.

Next, the decompression based on the Huffman coding or arithmetic codingis performed based on the unit of block, and the luminance signal Y andthe color difference signals Cb and Cr in the frequency space aregenerated (in step S32). The generated luminance signal Y is used forthe processing in steps S39 and S40, which will be described later.After the processing until step S46, which will be described later, theprocessing shifts to step S33. Similarly, the generated color differencesignals Cb and Cr are used for the processing in steps S39 and S40,which will be described later. After processing until step S46, whichwill be described later, the processing shifts to step S34.

That is, the luminance signal Y is inverting DCT transformed (in stepS33). The color difference signals Cb and Cr are inverting DCTtransformed (in step S34). Further, the color difference signals Cb andCr are up-sampled by a predetermined ratio (in step S35).

The luminance signal Y transformed in step S33 and the color differencesignals Cb and Cr up-sampled in step S34 are synthesized to generate theR, G, and B signals (in step S36). The synthesized R, G, and B signalsare outputted (in step S37).

Then, it is determined whether or not the processing ends for the entireblocks (in step S38). If the processing does not end, the processingreturns to step S32 whereupon the processing is executed as mentionedabove for the next block. If the processing ends, a series of processingends.

Next, a description is given of the noise reduction in steps S39 to S46with reference to FIG. 13B. As mentioned above, the processing iscommonly performed to the luminance signal Y and the color differencesignals Cb and Cr.

The zero-order component of the luminance signal Y or color differencesignals Cb and Cr is extracted (in step S39). The high-frequencycomponent except for the zero-order component of the luminance signal Yor color difference signals Cb and Cr is extracted (in step S40).

It is determined whether or not the noises are reduced based on theheader information read in step S31 (in step S41).

In the noise reduction, an average of the high-frequency component iscalculated (in step S42).

The amount of noises is calculated based on Formula 2 by using thezero-order component extracted in step S39 and the header informationread in step S31 (in step S43).

The allowable range is set based on Formula 4 (in step S44). The noisesare reduced based on Formula 5 (in step S45).

When step S45 ends or the noises are not reduced in step S41, it isdetermined whether or not the processing ends for the entirehigh-frequency components (in step S46). If the processing does not end,the processing returns to step S40 whereupon the above-mentionedprocessing is executed for another high-frequency component. If theprocessing ends, the processing shifts to step S33 or S34.

The independent replay system is described as mentioned above. However,the present invention is not limited to this. For example, the replaysystem may be combined to the image pickup system according to the firstor second embodiment to structure an image pickup replay system. In thiscase, the continuous photographing operation is fast by omitting thenoise reduction in the photographing operation. The noises areadditionally reduced after the photographing operation, therebyobtaining the high-quality image.

According to the third embodiment, the decompression using the frequencyspace and the noise reduction are integrated, thereby structuring thereplay system for obtaining the high-quality image with low costs.

Not only the zero-order component for calculating the amount of noisesis obtained every image but also various parameters such as thetemperature and the gain of the image pickup device in the photographingoperation on the amount of noises are obtained as the header informationfor each image. Further, the amount of noises is calculated based on theobtained information, thereby estimating the amount of noises with highprecision.

Only the signal having the estimated amount of noises or less issubjected to the smoothing processing, thereby effectively reducing thenoises.

Further, when the parameters the temperature and the gain forcalculating the amount of noises are not obtained, the standard value isused, thereby always reducing the noises.

FIGS. 14 and 15 show the fourth embodiment of the present invention.FIG. 14 is a block diagram showing the structure of an image pickupsystem. FIG. 15 is a flowchart showing the software processing forcorrecting the parameters for the noise reduction.

According to the fourth embodiment, the same portions as those accordingto the first to third embodiments are designated by the same referencenumerals, a description thereof is omitted, and only different portionsare described.

The image pickup system according to the fourth embodiment corrects theparameters for the noise reduction.

That is, referring to FIG. 14, the image pickup system according to thefourth embodiment is structured by deleting, from the structureaccording to the first embodiment, the block extracting unit 12, thezero-order quantizing unit 16, the noise estimating unit 20, the noisereducing unit 21, the high-frequency quantizing unit 22, and thecompressing unit 23. Further, the image pickup system according to thefourth embodiment comprises: a correcting image 80 having three types ormore of gray charts with different reflectances ranging white to black;a chart extracting unit 81, serving as chart separating means and blockextracting means, for extracting the chart from the video signal storedin the second buffer 11 and for outputting the extracted gray chart tothe Y/C separating unit 13; a variance calculating unit 82, serving asvariance calculating means, for calculating the variance of thehigh-frequency component extracted from the high-frequency extractingunit 19; and a fitting unit 83, serving as fitting means, for fittingthe output of the zero-order extracting unit 15 by using the variancecalculated by the variance calculating unit 82 and for transferring thefitted outputted to the output unit 24.

The fitting unit 83 in the additional structure is interactivelyconnected to the control unit 25 for control operation.

Next, a description is given of the signal flow in the image pickupsystem shown in FIG. 14.

After setting, via the external I/F unit 26, the ISO sensitivity and thephotographing condition such as an image quality mode, the correctingimage 80 is picked-up. In the photographing operation the photographingdistance is adjusted so as to view the correcting image 80 on the entirescreen and to uniformly irradiate illumination light on the entirecorrecting image 80. The video signal obtained by photographing thecorrecting image 80 is processed similarly to the first embodiment andis stored in the second buffer 11.

Next, the chart extracting unit 81 separates the gray charts in theimage signal on the entire screen, extracts the block area with apredetermined size, one-size smaller than the gray chart, as the graychart corresponding portion, and sequentially transfers the extractedgray charts to the Y/C separating unit 13. The portion corresponding tothe gray chart is automatically separated when the correcting image 80is adjusted to be viewed on the entire screen and when the arrangementof gray charts is well known.

The Y/C separating unit 13 transforms the R, G, and B signals into theluminance signal Y and the color difference signals Cb and Cr based onFormula 1. Then, the luminance signal Y is transferred to the luminanceDCT unit 14, and the color difference signals Cb and Cr are transferredto the color difference DCT unit 18 via the down-sampling unit 17.

As mentioned above, the luminance DCT unit 14 and the color differenceDCT unit 18 transform the signals in the real space into the signals inthe frequency space by the well-known DCT (Discrete Cosine Transform)transformation.

The zero-order extracting unit 15 sequentially extracts zero-ordercomponent of the luminance signal Y and the color difference signals Cband Cr of the signals transformed in the frequency space under thecontrol of the control unit 25, and the high-frequency extracting unit19 extracts the high-frequency component. The zero-order componentextracted by the zero-order extracting unit 15 is transferred to thefitting unit 83. The high-frequency component extracted by thehigh-frequency extracting unit 19 is transferred to the variancecalculating unit 82.

The variance calculating unit 82 calculates a variance value of thehigh-frequency component as a value corresponding to the amount ofnoises, and transfers the calculated variance value to the fitting unit83. The above-mentioned processing is executed for the entire graycharts.

The fitting unit 83 formulates the amount of noises under the control ofthe control unit 25, upon collecting, for the entire gray charts, theinformation on the zero-order component L extracted by the zero-orderextracting unit 15 and variance value N calculated by the variancecalculating unit 82. Here, as a formulation of the amount of noises, aformulation of [N=AL^(B)+C (where reference symbols A, B, and C denotethe constant terms)]. The formulation is performed by plotting thezero-order component L of the gray charts and the variance value N toobtain the constant terms A, B, and C with the well-known least squaresmethod. The constant terms are individually calculated for the threedata types of the luminance signal Y, the color difference signal Cb,and the color difference signal Cr.

The above-calculated constant terms A, B, and C are transferred,recorded, and stored to the output unit 24 serving as coefficientstoring means. This processing is executed for the entire combinationsof the image quality mode and the ISO sensitivity set via the externalI/F unit 26, thereby correcting the parameter for noise reduction.

The correction is performed on the hardware. However, the presentinvention is not limited to this. For example, the video signal from theCCD 4 may be outputted as the Raw data without processing. Further, theinformation on the temperature and the gain in the photographingoperation from the control unit 25 is outputted as the headerinformation and may be processed independently on software.

Next, a description is given of the software for correcting theparameter for noise reduction with reference to FIG. 15.

This processing starts, first, the video signal of the correcting image80 obtained as the Raw data and the header information such as thetemperature and the gain are read to the computer (in step S51).

General signal processing such as white balance, interpolation, andemphasis is executed (in step S52). Then, the corresponding portions ofthe gray charts are individually extracted (in step S53).

The video signal of the pixel in the gray chart is transformed into theluminance signal Y and the color signals Cb and Cr (in step S54).

The luminance signal Y among the transformed signals is transformed intoa signal in the frequency space by the DCT transformation (in step S55).The zero-order component is extracted (in step S56). The high-frequencycomponent except for the zero-order is extracted (in step S57). Thevariance value of the high-frequency component among the components iscalculated (in step S58).

Then, the zero-order component extracted in step S56 and the variancevalue calculated in step S58 are outputted (in step S59).

The color difference signals Cb and Cr separated in step S54 aredown-sampled by a predetermined ratio (in step S60). The colordifference signals Cb and Cr are DCT-transformed and are transformedinto a the signal in the frequency space (in step S61).

The zero-order component is extracted (in step S62). The high-frequencycomponent except for the zero-order component is extracted (in stepS63). The variance value of the high-frequency component among theextracted components is calculated (in step S64).

Next, the zero-order component extracted in step S62 and the variancevalue calculated in step S64 are outputted (in step S65).

Then, it is determined whether or not the processing ends for the entirecorresponding portions of the gray charts (in step S66). If theprocessing does not end, the processing returns to step S53 whereuponthe above-mentioned processing is executed for another correspondingportion of the gray chart.

If the processing ends for the entire corresponding portions of the graycharts, the fitting based on the least squares method is performed andthe parameters for noise reduction of the luminance signal Y and thecolor difference signals Cb and Cr are calculated (in step S67).

The parameters for noise reduction calculated in step S67 are outputted(in step S68), and a series of processing ends.

The formulation of the amount of noises uses the function of the powerindicated in Formula 2. However, the present invention is not limited tothe above function. For example, the formulation may use a quadraticexpression of [N=AL²+BL+C]. Alternatively, the formulation may useanother polynomial expression or sprine function.

According to the fourth embodiment, the parameter for noise reduction iseasily calculated by photographing the correcting image comprising thestandard gray scale. Therefore, the amount of noises can be estimatedwith high precision and flexibility even for a system withoutcalculation of parameter, the aging change in system, and the change insystem structure. For example, the structure according to the fourthembodiment is combined to that according to the third embodiment,thereby reducing the noises with high precision for the system withoutcalculation of parameter for noise reduction.

The parameter of the function for estimating the amount of noises isindependently stored and therefore the noises are reduced out of theimage pickup system.

The present invention is not limited to the above embodiments, and canvariously be modified or be applied without departing the range of theessentials of the present invention.

According to the present invention, as mentioned above, the image withthe high quality is fast captured with low costs.

Further, according to the present invention, the image with high qualityis captured flexibly corresponding to various systems.

1. An image pickup system comprising: a block extracting unit forextracting a block area with a predetermined size from a signal of animage pickup device; a transforming unit for transforming the signal inthe block area extracted by the block extracting unit into a signal in afrequency space; a noise estimator for estimating an amount of noise ofa frequency component except for a zero-order component based on azero-order component in the signal in the frequency space transformed bythe transforming unit; a noise reducing unit for reducing noise of thefrequency component except for the zero-order component based on theamount of noise estimated by the noise estimator; a compressing unit forcompressing the zero-order component and the frequency component exceptfor the zero-order component from which the noise is reduced, whereinthe block extracting unit comprises a chart separating unit forseparating a part corresponding to a gray chart from the signal obtainedby picking-up an image for correction including at least three types ofgray charts with different reflectances by the image pickup device, andthe transforming unit transforms the part corresponding to the graychart separated by the chart separating unit into the signal in thefrequency space, and the image pickup system further comprises: avariance calculating unit for calculating a variance N of the frequencycomponent except for the zero-order component of the corresponding partof the gray chart; and a fitting unit for calculating coefficients A, B,and C based on one of functional formulae N=AL^(B)+C and N=AL²+BL+Cwhere L is the zero-order component and N is the variance.
 2. An imagepickup system comprising: a block extracting unit for extracting a blockarea with a predetermined size from a signal of an image pickup device;a transforming unit for transforming the signal in the block areaextracted by the block extracting unit into a signal in a frequencyspace; a noise estimator for estimating an amount of noise of afrequency component except for a zero-order component based on azero-order component in the signal in the frequency space transformed bythe transforming unit; a noise reducing unit for reducing noise of thefrequency component except for the zero-order component based on theamount of noise estimated by the noise estimator; and a compressing unitfor compressing the zero-order component and the frequency componentexcept for the zero-order component from which the noise is reduced,wherein the block extracting unit comprises a chart separating unit forseparating a part corresponding to a gray chart from the signal obtainedby picking-up an image for correction including at least three types ofgray charts with different reflectances by the image pickup device, andthe transforming unit transforms the part corresponding to the graychart separated by the chart separating unit into the signal in thefrequency space, and the image pickup system further comprises: avariance calculating unit for calculating a variance N of the frequencycomponent except for the zero-order component of the corresponding partof the gray chart; and a fitting unit for calculating coefficients A, B,and C based on one of functional formulae N=AL^(B)+C and N=AL²+BL+Cusing a value L of where L is the zero-order component and N is thevariance; and further comprising: a coefficient storing unit for storingthe coefficients A, B, and C calculated by the fitting unit.
 3. A methodfor reducing noise in an image produced by an image pickup system havingan image pickup device configured to convert an optical image into asignal, comprising the steps of: a) extracting a block area of apredetermined size from a signal provided by an image pickup device; b)transforming the signal in the block area extracted in step (a) into asignal in a frequency space; c) estimating an amount of noise in afrequency component except for a zero-order component based on thezero-order component in the signal in the frequency space transformed atstep (b); d) reducing noise in the frequency component except for thezero-order component based on the amount of noise estimated at step (c);and e) compressing the zero-order component and the frequency componentexcept for the zero-order component from which the noise is reduced, andwherein step (d) further comprises: f) calculating an average of thefrequency component except for the zero-order component; g) setting anupper limit value and a lower limit value of the frequency componentexcept for the zero-order component based on the average calculated atstep (f) and the amount of noise estimated at step (c); and h)correcting the frequency component except for the zero-order componentbased on the upper limit value and the lower limit value set at step(g), and wherein step (a) further comprises: i) separating a partcorresponding to a gray chart from the signal obtained by picking-up animage for correction including at least three types of gray charts withdifferent reflectances by an image pickup device, and wherein step (b)transforms the part corresponding to the gray chart separated at step(i) into the signal in the frequency space, and the method furthercomprises the steps of: j) calculating a variance N of the frequencycomponent except for the zero-order component of the corresponding partof the gray chart; and k) calculating coefficients A, B, and C based onone of functional formulae of N=AL^(B)+C and N=AL²+BL+C by using a valueL of where L is the zero-order component and N is the variance.